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Atomic Emission Spectroscopy: Lab01:29

Atomic Emission Spectroscopy: Lab

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AES is a powerful analytical technique, especially effective when used with plasma sources, producing abundant spectra in characteristic emission lines. The Inductively Coupled Plasma (ICP), in particular, yields superior quantitative analytical data due to its high stability, low noise, low background, and minimal interferences under optimal experimental conditions. However, newer air-operated microwave sources are emerging as promising alternatives that could be more cost-effective than...
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Updated: Apr 16, 2026

Quantitative Analysis of Vacuum Induction Melting by Laser-induced Breakdown Spectroscopy
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[A multivariate nonlinear model for quantitative analysis in laser-induced breakdown spectroscopy].

Xing-Long Chen, Hong-Bo Fu, Jing-Ge Wang

    Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
    |March 11, 2015
    PubMed
    Summary
    This summary is machine-generated.

    A new multivariate nonlinear model for laser-induced breakdown spectroscopy (LIBS) analysis bypasses local thermal equilibrium (LTE) assumptions. This approach improves quantitative accuracy and repeatability in elemental analysis, particularly for materials like steel.

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    Area of Science:

    • Spectroscopy
    • Plasma Physics
    • Analytical Chemistry

    Context:

    • Quantitative analysis in laser-induced breakdown spectroscopy (LIBS) often relies on the assumption of local thermal equilibrium (LTE).
    • However, LTE is only achieved during a specific plasma evolution phase.
    • Deviations from LTE lead to inaccurate quantitative models, especially when using single spectral lines.

    Purpose:

    • To develop and validate a multivariate nonlinear model for LIBS quantitative analysis that does not require the assumption of local thermal equilibrium (LTE).
    • To compare the performance of this new model against traditional internal calibration models based on LTE.

    Summary:

    • A multivariate nonlinear model was proposed to mitigate signal fluctuations and enhance accuracy in quantitative LIBS analysis by removing the LTE requirement.
    • The model's efficacy was demonstrated by determining manganese (Mn) content in steel samples.
    • Results showed reduced error and relative standard deviation (RSD) compared to LTE-based methods.

    Impact:

    • The proposed multivariate nonlinear model significantly improves the accuracy and repeatability of quantitative analysis in laser-induced breakdown spectroscopy.
    • This advancement offers a more robust method for elemental determination in various materials, overcoming limitations of LTE-dependent models.